Determination of correlations in multivariate longitudinal data with modified Cholesky and hypersphere decomposition using Bayesian variable selection approach

Kuo Jung Lee, Ray Bing Chen, Min Sun Kwak, Keunbaik Lee

研究成果: Article同行評審

摘要

In this article, we present a Bayesian framework for multivariate longitudinal data analysis with a focus on selection of important elements in the generalized autoregressive matrix. An efficient Gibbs sampling algorithm was developed for the proposed model and its implementation in a comprehensive R package called MLModelSelection is available on the comprehensive R archive network. The performance of the proposed approach was studied via a comprehensive simulation study. The effectiveness of the methodology was illustrated using a nonalcoholic fatty liver disease dataset to study correlations in multiple responses over time to explain the joint variability of lung functions and body mass index. Supplementary materials for this article, including a standardized description of the materials needed to reproduce the work, are available as an online supplement.

原文English
頁(從 - 到)978-997
頁數20
期刊Statistics in Medicine
40
發行號4
DOIs
出版狀態Published - 2021 二月 20

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability

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